We have shown that our BERT-based local context model which implicitly captures entity type information and is effective in correcting two third of type error cases. It is nature to conjecture that we can also correct type errors by incorporating explicit type information into [1]} ganea2017deep. We investigate this approach in this section. Assuming that we have types for each mention and candidate entity, we calculate the Jaccard similarity between them and use it as a feature for local disambiguation model.
\({\rm JaccardSim}(e, m, c) = \frac{|T_m \cap T_e|}{|T_m \cup T_e|}\) 
